Parallel NoSQL Entity Resolution Approach with MapReduce

Kun Ma, Bo Yang
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引用次数: 6

Abstract

To address the limitation of entity resolution of NoSQL documents, we propose a new parallel NoSQL entity resolution approach with MapReduce. Although current MapReduce framework enables efficient parallel execution of entity resolution, it cannot find duplicates in adjacent block easily. Therefore, we investigate possible solutions called Partition-Sort-Map-Reduce to find duplicates by overlapping boundary objects in adjacent blocks. Finally, our experimental evaluation based on NoSQL breeding data and the analysis of time complexity show the high effectiveness and efficiency of the proposed entity resolution approaches.
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基于MapReduce的并行NoSQL实体解析方法
为了解决NoSQL文档实体解析的局限性,我们提出了一种新的基于MapReduce的并行NoSQL实体解析方法。虽然当前的MapReduce框架能够有效地并行执行实体解析,但它不能很容易地找到相邻块中的重复项。因此,我们研究了可能的解决方案,称为Partition-Sort-Map-Reduce,通过在相邻块中重叠边界对象来查找重复项。最后,基于NoSQL育种数据的实验评估和时间复杂度分析表明,本文提出的实体解析方法具有较高的有效性和高效性。
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